Simulating intervertebral disc cell behaviour within 3D multifactorial environments
| Autor: | Jérôme Noailly, J. J. Reagh, Laura Baumgartner, M. A. González Ballester |
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| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
Nucleus Pulposus Cell Survival Computer science Systems biology In silico Cell Intervertebral Disc Degeneration Computational biology Biochemistry 03 medical and health sciences 0302 clinical medicine medicine Humans Viability assay Intervertebral Disc Molecular Biology Cells Cultured Aggrecan 030304 developmental biology 0303 health sciences ADAMTS Experimental data Intervertebral disc Original Papers Computer Science Applications Computational Mathematics medicine.anatomical_structure Computational Theory and Mathematics 030217 neurology & neurosurgery |
| Zdroj: | Bioinformatics |
| ISSN: | 1367-4811 1367-4803 |
| DOI: | 10.1093/bioinformatics/btaa939 |
| Popis: | Motivation Low back pain is responsible for more global disability than any other condition. Its incidence is closely related to intervertebral disc (IVD) failure, which is likely caused by an accumulation of microtrauma within the IVD. Crucial factors in microtrauma development are not entirely known yet, probably because their exploration in vivo or in vitro remains tremendously challenging. In silico modelling is, therefore, definitively appealing, and shall include approaches to integrate influences of multiple cell stimuli at the microscale. Accordingly, this study introduces a hybrid Agent-based (AB) model in IVD research and exploits network modelling solutions in systems biology to mimic the cellular behaviour of Nucleus Pulposus cells exposed to a 3D multifactorial biochemical environment, based on mathematical integrations of existing experimental knowledge. Cellular activity reflected by mRNA expression of Aggrecan, Collagen type I, Collagen type II, MMP-3 and ADAMTS were calculated for inflamed and non-inflamed cells. mRNA expression over long periods of time is additionally determined including cell viability estimations. Model predictions were eventually validated with independent experimental data. Results As it combines experimental data to simulate cell behaviour exposed to a multifactorial environment, the present methodology was able to reproduce cell death within 3 days under glucose deprivation and a 50% decrease in cell viability after 7 days in an acidic environment. Cellular mRNA expression under non-inflamed conditions simulated a quantifiable catabolic shift under an adverse cell environment, and model predictions of mRNA expression of inflamed cells provide new explanation possibilities for unexpected results achieved in experimental research. Availabilityand implementation The AB model as well as used mathematical functions were built with open source software. Final functions implemented in the AB model and complete AB model parameters are provided as Supplementary Material. Experimental input and validation data were provided through referenced, published papers. The code corresponding to the model can be shared upon request and shall be reused after proper training. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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